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MUL TIVARJABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

MOHAMED OSMAN, MOHAMED ABDELRAHIM (2016) MUL TIVARJABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD. PhD thesis, Universiti Teknologi PETRONAS.

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Abstract

Channel isolation usmg partial correlation analysis and estimation of model parameters in the conventional multivariable closed-loop system identification approaches use the method of Least Square (LS) with the limitations, viz. (I) large estimation bias due to the highly correlated input signals, low Signal to Noise Ratio (SNR) and correlated noise signals; and (2) inconsistent parameter estimates due to noise and unmeasured disturbances. In this thesis. iterative Leaky Least Mean Squares (LLMS) based methods are proposed to address the limitations ofLS method in MultiInput Multi-Output (MIMO) closed-loop system identification. In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. All the proposed algorithms are demonstrated with the help of extensive simulation case studies and a real pilot-scale distillation column with appropriate validation procedures

Item Type: Thesis (PhD)
Academic Subject : Academic Department - Chemical Engineering - Separation Process
Subject: T Technology > TP Chemical technology
Divisions: Engineering > Chemical
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 16 Jan 2019 15:30
Last Modified: 16 Jan 2019 15:30
URI: http://utpedia.utp.edu.my/id/eprint/18328

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